The fitness cost and benefit of phase‐separated protein deposits
2019; Springer Nature; Volume: 15; Issue: 4 Linguagem: Inglês
10.15252/msb.20178075
ISSN1744-4292
AutoresNatalia Sánchez de Groot, Marc Torrent, Charles N. J. Ravarani, Ala Trusina, Salvador Ventura, M. Madan Babu,
Tópico(s)Heat shock proteins research
ResumoArticle8 April 2019Open Access Transparent process The fitness cost and benefit of phase-separated protein deposits Natalia Sanchez de Groot Corresponding Author Natalia Sanchez de Groot [email protected] orcid.org/0000-0002-0492-5532 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Spain Universitat Pompeu Fabra (UPF), Barcelona, Spain Search for more papers by this author Marc Torrent Burgas Marc Torrent Burgas orcid.org/0000-0001-6567-3474 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Systems Biology of Infection Lab, Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona, Spain Search for more papers by this author Charles NJ Ravarani Charles NJ Ravarani orcid.org/0000-0003-0952-3396 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Search for more papers by this author Ala Trusina Ala Trusina Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark Search for more papers by this author Salvador Ventura Salvador Ventura orcid.org/0000-0002-9652-6351 Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain Search for more papers by this author M Madan Babu Corresponding Author M Madan Babu [email protected] orcid.org/0000-0003-0556-6196 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Search for more papers by this author Natalia Sanchez de Groot Corresponding Author Natalia Sanchez de Groot [email protected] orcid.org/0000-0002-0492-5532 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Spain Universitat Pompeu Fabra (UPF), Barcelona, Spain Search for more papers by this author Marc Torrent Burgas Marc Torrent Burgas orcid.org/0000-0001-6567-3474 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Systems Biology of Infection Lab, Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona, Spain Search for more papers by this author Charles NJ Ravarani Charles NJ Ravarani orcid.org/0000-0003-0952-3396 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Search for more papers by this author Ala Trusina Ala Trusina Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark Search for more papers by this author Salvador Ventura Salvador Ventura orcid.org/0000-0002-9652-6351 Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain Search for more papers by this author M Madan Babu Corresponding Author M Madan Babu [email protected] orcid.org/0000-0003-0556-6196 Medical Research Council Laboratory of Molecular Biology, Cambridge, UK Search for more papers by this author Author Information Natalia Sanchez de Groot *,1,2,3,‡, Marc Torrent Burgas1,4,‡, Charles NJ Ravarani1, Ala Trusina5, Salvador Ventura6 and M Madan Babu *,1 1Medical Research Council Laboratory of Molecular Biology, Cambridge, UK 2Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Barcelona, Spain 3Universitat Pompeu Fabra (UPF), Barcelona, Spain 4Systems Biology of Infection Lab, Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Barcelona, Spain 5Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark 6Institut de Biotecnologia i Biomedicina and Departament de Bioquímica i Biologia Molecular, Universitat Autònoma de Barcelona, Barcelona, Spain ‡These authors contributed equally to this work *Corresponding author. Tel: +34 933160380; E-mail: [email protected] *Corresponding author. Tel: +44 1223 267066; E-mail: [email protected] Molecular Systems Biology (2019)15:e8075https://doi.org/10.15252/msb.20178075 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Phase separation of soluble proteins into insoluble deposits is associated with numerous diseases. However, protein deposits can also function as membrane-less compartments for many cellular processes. What are the fitness costs and benefits of forming such deposits in different conditions? Using a model protein that phase-separates into deposits, we distinguish and quantify the fitness contribution due to the loss or gain of protein function and deposit formation in yeast. The environmental condition and the cellular demand for the protein function emerge as key determinants of fitness. Protein deposit formation can influence cell-to-cell variation in free protein abundance between individuals of a cell population (i.e., gene expression noise). This results in variable manifestation of protein function and a continuous range of phenotypes in a cell population, favoring survival of some individuals in certain environments. Thus, protein deposit formation by phase separation might be a mechanism to sense protein concentration in cells and to generate phenotypic variability. The selectable phenotypic variability, previously described for prions, could be a general property of proteins that can form phase-separated assemblies and may influence cell fitness. Synopsis A model protein that phase separates into deposits is used to distinguish and quantify the fitness contribution due to the loss or gain of protein function and deposit formation in yeast. The presented approach identifies and quantifies different fitness effects associated with protein deposit formation due to phase separation. The environmental condition and the cellular demand for the protein function emerge as key determinants of fitness upon protein deposit formation. Variability in protein deposit formation can lead to cell-to-cell differences in free protein abundance between individuals. Protein phase separation can generate a continuous range of phenotypes in a cell population. Introduction The exposure of certain polypeptide segments in a protein to the solvent can trigger a process in which proteins phase-separate into macromolecular assemblies (Veis, 2011). The formation of protein deposits can affect biological processes as a result of a loss and/or gain of function and has been implicated in disorders such as Alzheimer's or Parkinson's disease (Chiti & Dobson, 2006; Jahn & Radford, 2008; Babu et al, 2011; Gsponer & Babu, 2012; Sanchez de Groot et al, 2012; Ciryam et al, 2013; Lin et al, 2015; Woerner et al, 2016). However, protein sequences predisposed to form deposits are found in all kingdoms of life suggesting a neutral or advantageous effect on cell fitness (Li et al, 2012; Newby & Lindquist, 2013; Berchowitz et al, 2015; Khan et al, 2015; Chavali et al, 2017a). In fact, it has been shown that phase separation-promoting sequences are essential to build membrane-less structures and higher-order assemblies with several biological functions (Maji et al, 2009; Bershtein et al, 2012; de Groot et al, 2012; Gsponer & Babu, 2012; Ciryam et al, 2013; Toretsky & Wright, 2014; Lin et al, 2015; Miller et al, 2015; Nott et al, 2015; Suresh et al, 2015; Wallace et al, 2015; Xiang et al, 2015; Zhu & Brangwynne, 2015; Chavali et al, 2017a; Holehouse & Pappu, 2018). Protein deposit formation due to phase separation inside the cell is a complex process that depends on a number of features such as the physicochemical properties of the polypeptide sequence (e.g., hydrophobicity, net charge; de Groot et al, 2006), local protein concentration (e.g., high vs. low concentration; Ciryam et al, 2013; Levy et al, 2014; Stepanenko et al, 2016), and its interaction with cellular components (e.g., chaperones, RNA; De Baets et al, 2011; Gsponer & Babu, 2012; Sanchez de Groot et al, 2012; Miller et al, 2015; Zhang et al, 2015; Jain et al, 2016; Pak et al, 2016; Maharana et al, 2018). The different combinations of these features result in the formation of deposits with different physicochemical and dynamic properties (Fig 1A). According to their viscoelastic characteristics and their ability to exchange components with the cytoplasm, protein assemblies can adopt a wide range of states that go from highly dynamic states with liquid droplet properties to almost static states with solid-like properties (Fig 1A; Franzmann et al, 2018). In this manner, phase-separated assemblies can be classified as liquid–liquid (e.g., nucleolus) or liquid–solid (e.g., amyloid aggregate) according to their viscoelastic and dynamic properties (e.g., deformation and coalescence; Morley et al, 2002; Jahn & Radford, 2008; Kaganovich et al, 2008; Escusa-Toret et al, 2013; Toretsky & Wright, 2014; Lin et al, 2015; Miller et al, 2015; Zhang et al, 2015; Zhu & Brangwynne, 2015; Jain et al, 2016; Boeynaems et al, 2018; Franzmann et al, 2018; Alberti et al, 2019). Figure 1. Model proteins and design of experimental system Protein phase separation can lead to the formation of protein assemblies with varying dynamics. Soluble proteins may phase-separate into liquid-like droplets or insoluble deposits that, according to their viscoelastic properties and their ability to exchange components with the cytoplasm, vary from being dynamic to static. Design of the modular system to measure the effect of protein phase separation on cell fitness. Growth media composition and the essential/non-essential/toxic roles of Ura3p. The model proteins consist of a fusion between Ura3p and GFP (URA3sol, left) and the amyloid-β-peptide of 42 residues (Aβ) (URA3agg, right). After 18 h of expression, Ura3psol remains homogeneously distributed whereas Ura3pagg is accumulated into intracellular foci. Download figure Download PowerPoint This variety of assemblies with distinct dynamic behavior (Fig 1A) is employed by cells to regulate key biological processes such as gametogenesis (Berchowitz et al, 2015), programmed necrosis (Li et al, 2012), hormone storage (Maji et al, 2009), or memory maintenance (Khan et al, 2015), among other functions (Toretsky & Wright, 2014; Miller et al, 2015; Chakrabortee et al, 2016; Mitrea & Kriwacki, 2016). Proteins that are able to phase-separate can perform their biological functions in the soluble state such as the pituitary hormones (Maji et al, 2009); the phase-separated state, such as the amyloid-like form of Rim4 (Berchowitz et al, 2015); or in both states (e.g., monomeric Orb2 represses, whereas oligomeric Orb2 activates translation; Khan et al, 2015). Therefore, the formation of phase-separated structures is not only associated with diseases but can positively influence cell fitness under different conditions. For instance, the recruitment of certain metabolic enzymes into cytoplasmic reservoirs/deposits enhances yeast survival during periods of starvation and stress (O'Connell et al, 2014; Petrovska et al, 2014; Suresh et al, 2015; Wallace et al, 2015; Riback et al, 2017; Franzmann et al, 2018). Thus, beyond prion domain-containing proteins, the extensive number of reported self-assembly events suggests that this is likely to be an intrinsic property of the polypeptide chain (Dobson, 1999; Monsellier et al, 2008). The ability for proteins to phase-separate tends to be encoded in specific regions or domains (Appendix Fig S1; Moore et al, 2008; Marsh & Teichmann, 2010; Li et al, 2012; Berchowitz et al, 2015; Khan et al, 2015; Hervas et al, 2016). Such a modular organization permits independent evolution of protein regions and facilitates the emergence of proteins with new properties through recombination (Moore et al, 2008; Marsh & Teichmann, 2010). The ultimate fitness consequences of phase-separated structures will depend on the function of the protein, the components sequestered in the assembly, dynamic nature, and the molecular structure of the phase-separated assembly, among other factors. Due to the complexity and the diverse effects associated with phase separation, there is a need to develop rational approaches that permit the quantification of the effects of forming such deposits on cell fitness in multiple environments and determine how proteins with phase separation-prone segments are selected for, or against, in a cell population. To begin unraveling the effect of these factors, we have designed a model protein that phase-separates to primarily form insoluble deposits and describe a population genetics approach. This allows us to disentangle and quantify the effect of the following factors associated with phase separation in different environments: the fitness change associated with (i) deposit formation, (ii) the loss of an essential biochemical activity of the protein that forms the deposit, and (iii) the gain of a beneficial effect due to deposit formation. Results Model for protein phase separation: one protein, three roles Various studies have reported diverse and often conflicting effects in terms of the beneficial and detrimental effects of protein deposit formation on cell fitness (Maji et al, 2009; Geiler-Samerotte et al, 2011; Sanchez de Groot et al, 2012; Escusa-Toret et al, 2013; Tomala et al, 2014). These differences are understandable if one considers the complexity of deposit formation, the differences in the dynamic nature of the deposit, biochemical function of the protein forming the deposit, and the diversity in the experimental conditions in which the studies have been carried out. Furthermore, prior studies in the literature typically do not explicitly discriminate the different phase separation processes or the different fitness effects associated with proteins (e.g., loss vs. gain of function due to deposit formation). Here, we measure and disentangle the effects of phase separation of a model protein. To trigger the phase separation process, instead of mutating an endogenous protein to destabilize it as has been done before (Geiler-Samerotte et al, 2011; Tomala et al, 2014), we designed a modular system that allows us to disentangle and quantify the cost/benefit of protein phase separation while tuning different roles influencing this process (e.g., the essentiality/non-essentiality/toxicity of a protein). The model protein phase-separates from a mainly soluble, functionally active state into a primarily insoluble, functionally less active state (Materials and Methods, Figs 5 and EV1, and Appendix Fig S2). Click here to expand this figure. Figure EV1. Protein levels and half-life of URA3sol and URA3agg. Analysis of the expression and the soluble/insoluble part of URA3sol and URA3agg. Total protein fraction obtained by two independent experiments after 18 h of induction. The number indicates the Ura3p concentration (upper bands) quantification normalized by the concentration of PGK1p (lower bands). URA3sol distribution is 88% soluble and 12% insoluble. URA3agg is 6% soluble and 94% insoluble. Band analysis has been done with ImageJ. In vivo degradation rate was measured as the fluorescence loss after induction inhibition (see the Materials and Methods section). The plot shows the fluorescence normalized by the concentration of cells (absorbance at 600 nm) at each time point. The slope (absolute value), standard error, and R2 of three technical replicates obtained from two different experiments are shown. The data were fitted to a Boltzmann's sigmoid. Download figure Download PowerPoint Mimicking the domain organization seen in nature (Derkatch et al, 1996; Moore et al, 2008; Marsh & Teichmann, 2010; Appendix Fig S1), our model protein is made up of three modular components (Fig 1B; Materials and Methods). The first component is a polypeptide segment whose biochemical activity can be essential, non-essential, or toxic for the cell. We chose the endogenous yeast enzyme orotidine-5′-phosphate decarboxylase (Ura3p) involved in the production of pyrimidine nucleotides and widely employed for positive and negative selection (Seiple et al, 2006; Fig 1C). Ura3p activity is essential in yeast cells that are grown in the absence of uracil. However, Ura3p activity is non-essential when grown in the presence of uracil. Furthermore, Ura3p activity is toxic in the presence of an alternative substrate named 5-fluoroorotic acid (5FOA), as it leads to the production of a toxic compound (5-fluorouracil, 5FU) leading to cell division arrest and cell death (Seiple et al, 2006; Fig 1C). The second component is a reporter (green fluorescent protein; GFP) that allows monitoring the integrity and the distribution/location of the protein in the cell (Fig 1B and D). The third component is a phase separation-promoting segment that leads to the formation of intracellular, insoluble protein deposits, which in our system is the 42-amino acid amyloid-β-peptide (Aβ) (de Groot & Ventura, 2006; Villar-Pique & Ventura, 2013; Sanchez de Groot et al, 2015; Fig 1D). We built two different constructs: one encoding Ura3p fused to GFP (to obtain a protein with no or low phase separation potential, Ura3psol) and another that includes the Aβ peptide to promote the phase separation process (Ura3pagg) (Fig 1D; Materials and Methods). Instead of using Ura3psol as a control, we initially considered fusing Ura3p-GFP to a soluble variant of the Aβ42 (Villar-Pique & Ventura, 2013; Sanchez de Groot et al, 2015; e.g., a non-foci-forming variant). However, the different soluble variants are not always completely soluble in yeast, since after fractionation they are still found in the insoluble part and they form deposits in some of the stress environments investigated in the current work (Villar-Pique & Ventura, 2013). Hence, we decided that the addition of a soluble variant of Aβ42 will not be a suitable control for generating the soluble version of Ura3p. We also decided against fusing another soluble protein with a length similar to Aβ42 but with a different sequence because URA3-GFP fusion is already a large protein and the inclusion of a "random" short soluble peptide sequence might not affect the cost significantly. We integrated the two chimeric genes (Ura3psol and Ura3pagg) into a stable genomic region (TRP1 locus) to ensure steady expression in multiple generations. We included an inducible promoter (GAL1) to control transcription and guarantee expression under different environments (Materials and Methods; Appendix Fig S2). Their integration in the S. cerevisiae genome resulted in two strains (URA3sol and URA3agg) with the same genomic background and with similar mRNA expression levels (Fig EV2). This ensures that the fitness cost of expressing the constructs as gratuitous proteins will remain similar in the two strains (Dekel & Alon, 2005; Pena et al, 2010; Plata et al, 2010; Geiler-Samerotte et al, 2011; Kafri et al, 2016) and hence minimally influence the measurements of fitness effects (next section). We monitored competitive growth and formation of deposits in different environments by changing the osmotic pressure (1 M sorbitol, 0.5 M NaCl), oxidation level (0.5 mM H2O2, 1 mM DTT), and temperature (37, 30 and 25°C) and in the presence of a chemical chaperone (0.5 M proline). After 18 h of induction at standard growth conditions (30°C) in mid-log phase, Ura3psol remains distributed through the cytoplasm, whereas Ura3pagg forms stable, non-dynamic protein deposits similar to IPODs (insoluble protein deposits; Kaganovich et al, 2008), as measured by FRAP experiments (Figs 1D and EV3). Although some of these assemblies may contain other proteins (Rothe et al, 2018), prior findings suggest that the vast majority of them are likely to be Ura3pagg (Morell et al, 2011; Sanchez de Groot et al, 2015). Click here to expand this figure. Figure EV2. Variation in transcript expression and PCR efficiency URA3sol and URA3agg have similar mRNA abundance according to the ΔΔCt method (Teste et al, 2009). These measurements were made with a pair of primers that anneal to a common region located in the GFP sequence, named primers FmRNA and RmRNA, respectively (Materials and Methods). The standard curves obtained for these primers are shown. Standard curves obtained for the population quantification (solF/solR primers for URA3sol cells and the aggF/aggR primers for URA3agg) (Materials and Methods). Download figure Download PowerPoint Click here to expand this figure. Figure EV3. Properties of URA3agg deposits using FRAPWe tested the consistency of the URA3agg foci by photobleaching one half of the deposit (green line and green square) and monitoring the protein diffusion from the other half (blue line and blue square) with confocal microscopy. The assay was monitored for 40 seconds and shows no fluorescence loss or gain in any of the sides. This indicates that these foci are very dense, very much like an insoluble protein deposit (IPOD; Kaganovich et al, 2008). A. Foci before (Time 0 s) and after (Time 40 s) photobleaching. B. Graph showing the fluorescence changes along time in each side of the foci. C, D. We also tested the conformation of the protein enclosed in the URA3agg foci by analyzing the binding of anti-oligomer antibodies (rabbit anti-oligomer (A11) AHB0052). As a secondary antibody, we used goat anti-rabbit IgG H&L tagged with an Alexa Fluor® 555 (ab150078). We obtained a bright fluorescence signal that colocalizes with the foci's GFP fluorescence, indicating that the deposits are rich in oligomeric structures. As a control, we also incubated URA3sol with these antibodies obtaining few faint Alexa Fluor foci at the cytoplasm, indicating the absence or very low presence of oligomers. Download figure Download PowerPoint Quantifying selection for/against phase separation in different environments We experimentally determined how the formation of intracellular protein deposits is selected for, or against, in a population when the two strains (URA3sol and URA3agg) are grown in competition (Fig 2A). We grew mixed cell cultures (1:1 initial proportion) for three days in exponential phase and measured the selection coefficient (S) by PCR (Fig 2A; Appendix Table S1; Materials and Methods; Chevin, 2011; Geiler-Samerotte et al, 2011; Sanchez de Groot et al, 2015). This growth phase will ensure a constant doubling time, a young population, and a low number of aged protein assemblies (Hill et al, 2016). The selection coefficient (S) is related to the difference in growth rate between the two strains (Fig 2B) and quantifies how much the cell fitness increases (positive values) or decreases (negative values) due to the formation of deposits in URA3agg in comparison with URA3sol. Figure 2. Protein phase separation and selection coefficient A. Experimental design to measure the selection coefficient (S) upon growing URA3agg in competition with URA3sol. B. The selection coefficient, S, is proportional to the difference in growth rates between URA3agg and URA3sol (Materials and Methods). ω is the growth rate, which corresponds to the inverse of doubling time, τ. C, D. The S-values measured at standard conditions (30°C) indicate that depending on the media composition (+Ura, −Ura, +5FOA), the formation of protein deposits can be neutral, deleterious, or even advantageous for the cell as the function becomes non-essential, essential or toxic, respectively. E. S-values measured in different environments. In all cases, the standard error is below 5%. See also Appendix Table S1. Color scale: purple in the absence of uracil (-Ura), white in the presence of uracil (+Ura), and orange in the presence of 5FOA (+5FOA). At 37°C, the heat stress together with the inability to fold Ura3p has such a strong fitness effect that the strains barely grew in the absence of uracil, impeding the measurement of S. A bar of purple-white diagonal lines indicates a presumed value of S at 37°C without uracil. Download figure Download PowerPoint The results obtained at standard growth conditions (30°C) show that the formation of Ura3pagg deposits can be neutral (in the presence of uracil; non-essential), deleterious (in the absence of uracil; essential), or even advantageous (in the presence of 5FOA; toxic) for yeast, depending on the composition of the growth medium (Fig 2C; average S-values from two biological replicates). Therefore, without changing the protein sequence or the genotype, we can quantify different overall effects of deposit formation on cell fitness (Fig 2D). In this manner, the system we developed allows for the quantification of the overall effects (both negative and positive fitness effects) of deposit formation upon protein phase separation in different environments (Fig 2E and Appendix Table S1). We find a wide range of selection coefficients suggesting that URA3agg is differentially selected for or against when the role of the protein is different (essential/non-essential/toxic; in different media) and in different environments (Fig 2E). Changing the oxidation levels (0.5 mM H2O2, 1 mM DTT) or increasing the temperature (37°C) has a major effect on fitness compared to conditions in which we changed the osmotic pressure (1 M sorbitol, 0.5 M NaCl), or decreased the temperature (25°C) or when we added a chemical chaperone (0.5 M proline). This observation raises the question as to how and why the phase separation of the same protein leads to such differences in selection coefficients under different environments. We investigate this question in the next sections (Fig EV4). Click here to expand this figure. Figure EV4. Summary of the effects associated with URA3agg phase separation in different environments that affect the topology of Ura3p, and hence protein activity (supply) as well as the cell state (demand) Diagram showing different activity associated with the free and deposited protein. Summary table of the effects associated with Ura3pagg deposition and their effects on the selection outcome when growing in competition with URA3sol. Download figure Download PowerPoint Disentangling the different effects of protein phase separation The overall fitness effect (cost/benefit) of protein phase separation is not only determined by the loss or gain of the biochemical activity of the protein, but also due to the cost of deposit formation (e.g., amino acid sequestration in deposits, sequestration of ATP-dependent chaperone activity and other proteins, toxicity of the assembly; Maji et al, 2009; Olzscha et al, 2011;; Gsponer & Babu, 2012; Sanchez de Groot et al, 2012; Suraweera et al, 2012; Tomala et al, 2014; Patel et al, 2017); Fig 3A, equation 1). To infer the impact of these effects, we considered that the measured selection coefficient (S) is determined by a combination of three factors: (i) the cost of deposit formation, (ii) the cost of losing the essential Ura3p biochemical activity, and (iii) the benefit of gaining a protective function against the toxic activity by sequestering Ura3p into deposits (Fig 3A, equation 2). In conditions where Ura3p is not essential (with uracil), any change in cell fitness primarily depends on the fitness cost of deposit formation (Fig 3A, equation3). In the absence of uracil, the overall effect on fitness includes not only the cost of deposit formation but also the cost of reducing Ura3p activity due to deposit formation (Fig 3, equation 4). Finally, in the presence of 5FOA, the effect on fitness includes the cost of deposit formation, and the fitness benefit of reducing the toxic activity of Ura3p by sequestering the protein into the deposit (Fig 3, equation 5). Although some Ura3p activity can be present in deposits (O'Connell et al, 2014; Wallace et al, 2015), this is likely to be significantly reduced (e.g., due to protein conformational changes, and restricted access to substrate) compared to the free, diffusible well-folded protein as in the URA3sol strain (Suresh et al, 2015). Figure 3. Fitness cost and benefit analysis We measured the intensity of fluorescence emitted by the fluorescent reporter (GFP) to estimate (i) the amount, (ii) the location, and (iii) the deposited/diffused state of the model proteins. Accordingly, for each cell analyzed, we measured the fluorescence intensity of its cytoplasm (FTOTALsol for URA3sol and FCYTOagg for URA3agg) and of its foci (FFOCIagg). We used these measurements to estimate the different effects of protein phase separation on cell fitness. The overall fitness effect of forming a protein deposit depends on three factors: foci formation, loss of function, and gain of function (Equation 1). In our system, we can distinguish between the cost of forming Ura3p deposits, cost of losing the essential Ura3p activity, and the benefit from protection against Ura3p toxicity. Each cost and benefit effect depends on the ratio of deposited or free protein and the specific environment. Accordingly, we can split these cost and benefit effects into two components: one associated with the amount of deposited or free protein (FFOCIagg/FTOTALagg or FCYTOagg/FTOTALsol) and a magnitude of effect defined by the environmental conditions (α, β, or γ) (Equation 2). For the non-essential, essential, and toxic roles (+Ura, −Ura, and +5FOA) of Ura3p, the number and type of effects applicable are different (equations 3-5). Plots showing the distribution and relationship between the fractions of deposited or free Ura3p, its magnitude of effect on fitness (α/β/γ), and the selection coefficient (S) in different environments. Average of the selection coefficient (left) and average of the cytos
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